Technical Note This release presents labor force and unemployment data for census regions and divisions, states, and selected substate areas from the Local Area Unemployment Statistics (LAUS) program (tables 1 to 4). Also presented are nonfarm payroll employment estimates by state and industry supersector from the Current Employment Statistics (CES) program (tables 5 and 6). The LAUS and CES programs are both federal-state cooperative endeavors. Labor force and unemployment--from the LAUS program Definitions. The labor force and unemployment data are based on the same concepts and definitions as those used for the official national estimates obtained from the Current Population Survey (CPS), a sample survey of households that is conducted for the Bureau of Labor Statistics (BLS) by the U.S. Census Bureau. The LAUS program measures employment and unemployment on a place-of-residence basis. The universe for each is the civilian noninstitutional population 16 years of age and over. Employed persons are those who did any work at all for pay or profit in the reference week (the week including the 12th of the month) or worked 15 hours or more without pay in a family business or farm, plus those not working who had a job from which they were temporarily absent, whether or not paid, for such reasons as bad weather, labor-management dispute, illness, or vacation. Unemployed persons are those who were not employed during the reference week (based on the definition above), had actively looked for a job sometime in the 4-week period ending with the reference week, and were currently available for work; persons on layoff expecting recall need not be looking for work to be counted as unemployed. The labor force is the sum of employed and unemployed persons. The unemployment rate is the number of unemployed as a percent of the labor force. Method of estimation. Estimates for 48 of the 50 states, the District of Columbia, the Los Angeles-Long Beach-Glendale metropolitan division, New York City, and the balances of California and New York State are produced using time-series models. This method, which underwent substantial enhancement at the beginning of 2015, utilizes data from several sources, including the CPS, the CES, and state unemployment insurance (UI) programs. Estimates for the state of California are derived by summing the estimates for the Los Angeles-Long Beach-Glendale metropolitan division and the balance of California. Similarly, estimates for New York State are derived by summing the estimates for New York City and the balance of New York State. Estimates for the nine census divisions, as well as the five additional substate areas contained in this release (the Cleveland-Elyria and Detroit-Warren-Dearborn metropolitan areas and the Chicago-Naperville-Arlington Heights, Miami-Miami Beach-Kendall, and Seattle-Bellevue-Everett metropolitan divisions) and their respective balances of state are based on similar model-based approaches. Estimates for census regions are obtained by summing the model-based estimates for the component divisions. Each month, census division estimates are controlled to the national totals; state estimates are then controlled to their respective division totals. Substate and balance-of-state estimates for the five areas noted above are controlled to their respective state totals. Estimates for Puerto Rico are derived from a monthly household survey similar to the CPS. A detailed description of the estimation procedures is available from BLS upon request. Annual revisions. Labor force and unemployment data for prior years reflect adjustments made at the end of each year. The adjusted estimates reflect updated population data from the U.S. Census Bureau, any revisions in the other data sources, and model re-estimation. In most years, historical data for the most recent five years (both seasonally adjusted and not seasonally adjusted) are revised near the beginning of each calendar year, prior to the release of January estimates. With the introduction of a new generation of times-series models in early 2015, historical data were re-estimated back to the series beginnings in 1976, 1990, or 1994. Seasonal adjustment. The LAUS program introduced smoothed seasonally adjusted (SSA) estimates in January 2010. These are seasonally adjusted data that have incorporated a long-run trend smoothing procedure, resulting in estimates that are less volatile than those previously produced. The estimates are smoothed using a Henderson Trend Filter (H13). The H13 uses a filtering procedure, based on moving averages, to remove the irregular fluctuations from the seasonally adjusted series, leaving the trend. The same process is used on both historical and current year estimates. For more information about the smoothing technique, see the BLS website at www.bls.gov/lau/lassaqa.htm. Area definitions. The substate area data published in this release reflect the delineations issued by the U.S. Office of Management and Budget on February 28, 2013. A detailed list of the geographic definitions is available online at www.bls.gov/lau/lausmsa.htm. Employment--from the CES program Definitions. Employment data refer to persons on establishment payrolls who receive pay for any part of the pay period that includes the 12th of the month. Persons are counted at their place of work rather than at their place of residence; those appearing on more than one payroll are counted on each payroll. Industries are classified on the basis of their principal activity in accordance with the 2012 version of the North American Industry Classification System. Method of estimation. CES State and Area employment data are produced using several estimation procedures. Where possible these data are produced using a "weighted link relative" estimation technique in which a ratio of current month weighted employment to that of the previous-month weighted employment is computed from a sample of establishments reporting for both months. The estimates of employment for the current month are then obtained by multiplying these ratios by the previous month's employment estimates. The weighted link relative technique is utilized for data series where the sample size meets certain statistical criteria. For some employment series, the sample of establishments is very small or highly variable. In these cases, a model-based approach is used in estimation. These models use the direct sample estimates (described above), combined with forecasts of historical (benchmarked) data to decrease volatility in estimation. Two different models (Fay-Herriot Model and Small Domain Model) are used depending on the industry level being estimated. For more detailed information about each model, refer to the BLS Handbook of Methods. Annual revisions. Employment estimates are adjusted annually to a complete count of jobs, called benchmarks, derived principally from tax reports that are submitted by employers who are covered under state unemployment insurance (UI) laws. The benchmark information is used to adjust the monthly estimates between the new benchmark and the preceding one and also to establish the level of employment for the new benchmark month. Thus, the benchmarking process establishes the level of employment, and the sample is used to measure the month-to-month changes in the level for the subsequent months. Seasonal adjustment. Payroll employment data are seasonally adjusted at the statewide supersector level. In some states, the seasonally adjusted payroll employment total is computed by aggregating the independently adjusted supersector series. In other states, the seasonally adjusted payroll employment total is independently adjusted. Revisions of historical data for the most recent 5 years are made once a year, coincident with annual benchmark adjustments. Caution on aggregating state data. State estimation procedures are designed to produce accurate data for each individual state. BLS independently develops a national employment series; state estimates are not forced to sum to national totals. Because each state series is subject to larger sampling and nonsampling errors than the national series, summing them cumulates individual state level errors and can cause significant distortions at an aggregate level. Due to these statistical limitations, BLS does not compile a "sum- of-states" employment series, and cautions users that such a series is subject to a relatively large and volatile error structure. Reliability of the estimates The estimates presented in this release are based on sample surveys, administrative data, and modeling and, thus, are subject to sampling and other types of errors. Sampling error is a measure of sampling variability--that is, variation that occurs by chance because a sample rather than the entire population is surveyed. Survey data also are subject to nonsampling errors, such as those which can be introduced into the data collection and processing operations. Estimates not directly derived from sample surveys are subject to additional errors resulting from the specific estimation processes used. The sums of individual items may not always equal the totals shown in the same tables because of rounding. Unemployment rates are computed from unrounded data and thus may differ slightly from rates computed using the rounded data displayed in the tables. Use of error measures. The introductory section of this release preserves the long- time practice of highlighting the direction of the movements in regional and state unemployment rates and state nonfarm payroll employment regardless of their statistical significance. The remainder of the analysis in the release takes statistical significance into consideration. Labor force and unemployment estimates. Model-based error measures for seasonally adjusted and not seasonally adjusted data and for over-the-month and over-the-year changes are available online at www.bls.gov/lau/lastderr.htm. BLS uses a 90-percent confidence level in determining whether changes in LAUS unemployment rates are statistically significant. The average magnitude of the current year over-the-month change in a state unemployment rate that is required for statistical significance at the 90-percent confidence level is just over 0.2 percentage point; the average amount of the current over-the-year change in a state rate for significance is about 0.7 point. More details can be found on the website. Measures of nonsampling error are not available. Employment estimates. Measures of sampling error for state CES data at the total nonfarm and supersector levels are available online at www.bls.gov/sae/790stderr.htm. BLS uses a 90-percent confidence level in determining whether changes in CES employment levels are statistically significant. Information on recent benchmark revisions for states is available online at www.bls.gov/sae/benchmark2016.pdf. Additional information Estimates of labor force and unemployment from the LAUS program, as well as nonfarm employment from the CES program, for 394 metropolitan areas and metropolitan New England City and Town Areas (NECTAs) are available in the news release, Metropolitan Area Employment and Unemployment. Estimates of labor force, employment, and unemployment for approximately 7,500 subnational areas are available online at www.bls.gov/lau/. Employment data from the CES program for states and metropolitan areas are available online at www.bls.gov/sae/. Information in this release will be made available to sensory impaired individuals upon request. Voice phone: (202) 691-5200; Federal Relay Service: (800) 877-8339.